What are the major phases in Project Management

Project Management Major Phases

Project Management Major Phases

 

Per the Project Management Institute (PMI), there are five phases of project management and if the lifecycle provides a high-level view of the project, the phases are the roadmap to accomplishing it.

Major Phases in Project Management

  1. Initiating
  2. Planning
  3. Executing
  4. Monitoring and Controlling
  5. Closing

Related References

Project Management Institute (PMI)

Learning, Library

Project Management – What Is Agile?

 

Agile Project Management Methodology

Agile Project Management Methodology

 

What Is Agile?

At its core, agile is an iterative project management methodology. Agile works by breaking projects down into short duration milestones of user functionality, prioritizing them, and then continuously delivering iterations, usually, in short two week cycles.

Related References

 

 

Repeatable Project Management

Effective project management is a repeatable process

Project Management

 

Effective project management is a repeatable process.

 

–by Bonnie McCullough, “Totally Organized The Bonnie McCullough way: Easy-To-Use proven techniques for getting Control of Your Time and Your Home”, 1986 ISBN: 0-312-807747-3

Project Management – Data Warehouse Project Plan Template

Project Management

Project Management

 

While I’m no longer a formal Project Manager, from time to time I still have the need to create a project Plan or to help someone else to organize a project plan.  Usually. I find that it is easier to get to a more holistic plan faster, if I have a pattern of essential tasks and milestone to work with.  So, I usually go to a template which I have assembled across time use as an accelerator and/or job aide.   The attached project plan templates are for a common data warehouse project pattern, but by no means is intended to be the end all of project plans; it is just a starter kick, sort of speak.

There are several reasons why projects plan patterns may vary, other than the experience and knowledge of project planner, among them are:

  • The environment migration pattern in use
  • The application stack of the of the environment
  • The tools use to manage the project plan (MS Project, JIRA, OpenProj, etc.)
  • The size and complexity of the project team

Here is project plan mockup around Infosphere Datastage, but should be adaptable to any other ETL application.

XML Version of the Plan

OpenProj Version of the plan

Software Development Life Cycle – What is RAD?

Acronyms, Abbreviations, Terms, And Definitions

Acronyms, Abbreviations, Terms, And Definitions

What is RAD?

Rapid Application Development (RAD) is a type of incremental software development methodology, which emphasizes rapid prototyping and iterative delivery, rather than planning. In RAD model the components or major functions are developed in parallel as if they were small relatively independent projects, until integration.

RAD projects are iterative and incremental

RAD projects follow the SDLC iterative and incremental model:

  • During which more than one iteration of the software development cycle may be in progress at the same time
  • In RAD model the functional application modules are developed in parallel, as prototypes, and are integrated to complete the product for faster product delivery.
  • RAD teams are small and comprised of developers, domain experts, customer representatives and other information technology resources working progressively on their component and/or prototype.

Common Information Integration Testing Phases

Over the years I have seen a lot of patterns for Information integration testing process and these patterns will not be an exhaustive list of patterns a consultant will encounter over the course of a career.

However, two most common patterns in the testing process are:

The Three Test Phase Pattern

In the three test phase pattern, normally, the environment and testing activities of SIT and SWIT are combined.

The Three Test Phase Pattern

The Three Test Phase Pattern

The Four Test Phase Pattern

In the four test phase pattern, normally, the environment and testing activities of SIT and SWIT are performed separately and, frequently, will have separate environments in the migration path.

The Four Test Phase Pattern

The Four Test Phase Pattern

Testing Phases

Unit Testing:

Testing of individual software components or modules. Typically done by the programmer and not by testers, as it requires detailed knowledge of the internal program design and code. may require developing test driver modules or test harnesses.

 System Integration Testing (SIT):

Integration testing – Testing of integrated modules to verify combined functionality after integration. Modules are typically code modules, individual applications, client and server applications on a network, etc. This type of testing is especially relevant to client/server and distributed systems. Testing performed to expose defects in the interfaces and in the interactions between integrated components or systems. See also component integration testing, system integration testing.

 Software Integration Test (SWIT)

Similar to system testing, involves testing of a complete application environment, including scheduling, in a situation that mimics real-world use, such as interacting with a database, using network communications, or interacting with other hardware, applications, or systems if appropriate.

 User Acceptance Testing (UAT):

Normally, this type of testing is done to verify if the system meets the customer specified requirements. Users or customers do this testing to determine whether to accept the application.  Formal testing with respect to user needs, requirements, and business processes conducted to determine whether or not a system satisfies the acceptance criteria and to enable the user, customers or other authorized entity to determine whether or not to accept the system.

Related References

 

 

Data Modeling – What is Data Modeling?

Data Models, Data Modeling, What is data Modeling, logical Model, Conceptual Model, Physical Model

Data Models

Data modeling is the documenting of data relationships, characteristics, and standards based on its intended use of the data.   Data modeling techniques and tools capture and translate complex system designs into easily understood representations of the data creating a blueprint and foundation for information technology development and reengineering.

A data model can be thought of as a diagram  that illustrates the relationships between data. Although capturing all the possible relationships in a data model can be very time-intensive, a well-documented models allow stakeholders to identify errors and make changes before any programming code has been written.

Data modelers often use multiple models to view the same data and ensure that all processes, entities, relationships and data flows have been identified.

There are several different approaches to data modeling, including:

Concept Data Model (CDM)

  • The Concept Data Model (CDM) identifies the high level information entities, their relationships, and organized in the Entity Relationship Diagram (ERD).

Logical Data Model (LDM)

  • The Logical Data Model (LDM)  defines detail business information (in business terms) within each of the Concept Data Model and is a refinement of the information entities of the Concept Data Model.   Logical data model are non-RDBMS specific  business definition of tables, fields, and attributes contained within each information entity from which the Physical Data Model (PDM) and Entity Relationship Diagram (ERD) is produced.

Physical Data Model (PDM)

  • The Physical Data Model (PDM)  provides the actual technical details of the model and database object (e.g. table names, field names, etc.) to facilitate creation of accurate detail technical designs and actual database creation.  Physical Data Models are RDBMS specific definition of the logical model used build database, create deployable DDL statements, and to produce the Entity Relationship Diagram (ERD).

Related References

 

Where do data models fit in the Software Development Life Cycle (SDLC) Process?

Data Model SDLC Relationship Diagram

Data Model SDLC Relationship Diagram

In the classic Software Development Life Cycle (SDLC) process, Data Models are typically initiated, by model type, at key process steps and are maintained as data model detail is added and refinement occurs.

The Concept Data Model (CDM) is, usually, created in the Planning phase.   However,  creation the Concept Data Model  can slide forwarded or backward,  somewhat , within the System Concept Development, Planning, and Requirements Analysis phases, depending upon  whether the application being modeled is a custom development effort or a modification of a Commercial-Off-The-Shelf (COTS) application.  The CDM is maintained, as necessary, through the remainder of the SDLC process.

The Logical Data Model (LDM) is created in the Requirement Analysis phase and is a refinement of the information entities of the Concept Data Model. The LDM is maintained, as necessary, through the remainder of the SDLC process.

The Physical Data Model (PDM) is created in the Design phase to facilitate creation of accurate detail technical designs and actual database creation. The PDM is maintained, as necessary, through the remainder of the SDLC process.

Related References: